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Add Vision Logo detection.
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‎docs/index.rst‎

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vision-usage
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vision-client
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vision-image
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vision-entity
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vision-feature
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vision-face
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‎docs/vision-entity.rst‎

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Vision Entity
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=============
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Entity
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~~~~~~
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.. automodule:: google.cloud.vision.entity
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:members:
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:undoc-members:
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:show-inheritance:

‎google/cloud/vision/entity.py‎

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# Copyright 2016 Google Inc. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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"""Entity class for holding information returned from annotating an image."""
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from google.cloud.vision.geometry import Bounds
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class EntityAnnotation(object):
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"""Representation of an entity returned from the Vision API.
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:type bounds: dict
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:param bounds: Dictionary of bounary information of detected entity.
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:type description: str
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:param description: Description of entity detected in an image.
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:type mid: str
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:param mid: Opaque entity ID.
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:type score: float
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:param score: Overall score of the result. Range [0, 1].
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"""
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def __init__(self, bounds, description, mid, score):
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self._bounds = bounds
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self._description = description
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self._mid = mid
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self._score = score
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@classmethod
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def from_api_repr(cls, response):
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"""Factory: construct entity from Vision API response.
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:type response: dict
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:param response: Dictionary response from Vision API with entity data.
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:rtype: :class:`~google.cloud.vision.entiy.EntityAnnotation`
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:returns: Instance of ``EntityAnnotation``.
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"""
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bounds = Bounds.from_api_repr(response['boundingPoly'])
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description = response['description']
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mid = response['mid']
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score = response['score']
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return cls(bounds, description, mid, score)
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@property
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def bounds(self):
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"""Bounding polygon of detected image feature.
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:rtype: :class:`~google.cloud.vision.geometry.Bounds`
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:returns: Instance of ``Bounds`` with populated vertices.
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"""
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return self._bounds
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@property
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def description(self):
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"""Description of feature detected in image.
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:rtype: str
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:returns: String description of feature detected in image.
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"""
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return self._description
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@property
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def mid(self):
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"""MID of feature detected in image.
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:rtype: str
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:returns: String MID of feature detected in image.
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"""
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return self._mid
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@property
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def score(self):
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"""Overall score of the result. Range [0, 1].
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:rtype: float
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:returns: Overall score of the result. Range [0, 1].
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"""
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return self._score

‎google/cloud/vision/feature.py‎

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self._max_results = int(max_results)
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def as_dict(self):
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"""Generate dictionary for Feature request format."""
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"""Generate dictionary for Feature request format.
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:rtype: dict
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:returns: Dictionary representation of a
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:class:`~google.cloud.vision.feature.FeatureType`.
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"""
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return {
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'type': self.feature_type,
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'maxResults': self.max_results
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}
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@property
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def feature_type(self):
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""""Feature type string."""
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""""Feature type string.
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:rtype: :class:`~google.cloud.vision.feature.FeatureTypes`
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:returns: Instance of
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:class:`~google.cloud.vision.feature.FeatureTypes`
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"""
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return self._feature_type
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@property
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def max_results(self):
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"""Maximum number of results for feature type."""
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"""Maximum number of results for feature type.
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:rtype: int
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:returns: Maxium results to be returned.
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"""
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return self._max_results

‎google/cloud/vision/geometry.py‎

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class BoundsBase(object):
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"""Base class for handling bounds with vertices."""
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"""Base class for handling bounds with vertices.
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:type vertices: list of :class:`~google.cloud.vision.geometry.Vertex`
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:param vertices: List of vertcies describing points on an image.
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"""
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def __init__(self, vertices):
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self._vertices = vertices
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def vertices(self):
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"""List of vertices.
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:rtype: list
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:rtype: list of :class:`~google.cloud.vision.geometry.Vertex`
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:returns: List of populated vertices.
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"""
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return self._vertices
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class Bounds(BoundsBase):
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"""A polygon boundry of the detected feature."""
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class FDBounds(BoundsBase):
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"""The bounding polygon of just the skin portion of the face."""
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class Position(object):
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"""A 3D position in the image.
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See:
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https://cloud.google.com/vision/reference/rest/v1/images/annotate#Position
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:type x_coordinate: float
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:param x_coordinate: X position coordinate.
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:type y_coordinate: float
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:param y_coordinate: Y position coordinate.
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:type z_coordinate: float
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:param z_coordinate: Z position coordinate.
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"""
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def __init__(self, x_coordinate, y_coordinate, z_coordinate):
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self._x_coordinate = x_coordinate
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https://cloud.google.com/vision/reference/rest/v1/images/annotate#Vertex
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:type x_coordinate: float
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:param x_coordinate: X position coordinate.
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:type y_coordinate: float
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:param y_coordinate: Y position coordinate.
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"""
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def __init__(self, x_coordinate, y_coordinate):
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self._x_coordinate = x_coordinate

‎google/cloud/vision/image.py‎

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from base64 import b64encode
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from google.cloud._helpers import _to_bytes
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from google.cloud.vision.entity import EntityAnnotation
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from google.cloud.vision.face import Face
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from google.cloud.vision.feature import Feature
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from google.cloud.vision.feature import FeatureTypes
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faces.append(face)
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return faces
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def detect_logos(self, limit=10):
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"""Detect logos in an image.
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:type limit: int
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:param limit: The maximum number of logos to find.
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:rtype: list
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:returns: List of
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:class:`~google.cloud.vision.entity.EntityAnnotation`.
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"""
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logos = []
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logo_detection_feature = Feature(FeatureTypes.LOGO_DETECTION, limit)
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result = self.client.annotate(self, [logo_detection_feature])
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for logo_response in result['logoAnnotations']:
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logo = EntityAnnotation.from_api_repr(logo_response)
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logos.append(logo)
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return logos

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